1. Discussion (Chapter 3): Why are the original/raw data not readily usable by analytics tasks? What are the main data preprocessing steps? List and explain their importance in analytics.
2. How do you describe the importance of data in analyt-ics? Can we think of analytics without data? Explain.
3. Considering the new and broad definition of business analytics, what are the main inputs and outputs to the analytics continuum?
4. Where do the data for business analytics come from? What are the sources and the nature of those incoming data?
5. What are the most common metrics that make for analytics-ready data
6. Go to data.gov—a U.S. government–sponsored data portal that has a very large number of data sets on a wide variety of topics ranging from healthcare to edu-cation, climate to public safety. Pick a topic that you are most passionate about. Go through the topic-specific information and explanation provided on the site. Explore the possibilities of downloading the data, and use your favorite data visualization tool to create your own meaningful information and visualizations.
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Beyond the EU: DORA and NIS 2 Directive's Global Impact
1. Discussion (Chapter 3) Why are the originalraw data not readily.docx
1. 1. Discussion (Chapter 3): Why are the original/raw data not
readily usable by analytics tasks? What are the main data
preprocessing steps? List and explain their importance in
analytics.
2. How do you describe the importance of data in analyt-ics?
Can we think of analytics without data? Explain.
3. Considering the new and broad definition of business
analytics, what are the main inputs and outputs to the analytics
continuum?
4. Where do the data for business analytics come from? What
are the sources and the nature of those incoming data?
5. What are the most common metrics that make for analytics-
ready data
6. Go to data.gov—a U.S. government–sponsored data portal
that has a very large number of data sets on a wide variety of
topics ranging from healthcare to edu-cation, climate to public
safety. Pick a topic that you are most passionate about. Go
through the topic-specific information and explanation provided
on the site. Explore the possibilities of downloading the data,
and use your favorite data visualization tool to create your own
meaningful information and visualizations.
